Helper function to identify duplicate forecasts, i.e. instances where there is more than one forecast for the same prediction target.
Arguments
- data
A data.frame as used for
score()- forecast_unit
A character vector with the column names that define the unit of a single forecast. If missing the function tries to infer the unit of a single forecast.
Examples
example <- rbind(example_quantile, example_quantile[1000:1010])
find_duplicates(example)
#> location target_end_date target_type true_value location_name forecast_date
#> 1: DE 2021-05-22 Deaths 1285 Germany 2021-05-17
#> 2: DE 2021-05-22 Deaths 1285 Germany 2021-05-17
#> 3: DE 2021-05-22 Deaths 1285 Germany 2021-05-17
#> 4: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 5: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 6: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 7: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 8: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 9: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 10: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 11: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 12: DE 2021-05-22 Deaths 1285 Germany 2021-05-17
#> 13: DE 2021-05-22 Deaths 1285 Germany 2021-05-17
#> 14: DE 2021-05-22 Deaths 1285 Germany 2021-05-17
#> 15: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 16: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 17: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 18: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 19: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 20: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 21: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> 22: DE 2021-05-29 Cases 31653 Germany 2021-05-10
#> location target_end_date target_type true_value location_name forecast_date
#> quantile prediction model horizon
#> 1: 0.950 1464 epiforecasts-EpiNow2 1
#> 2: 0.975 1642 epiforecasts-EpiNow2 1
#> 3: 0.990 1951 epiforecasts-EpiNow2 1
#> 4: 0.010 28999 EuroCOVIDhub-ensemble 3
#> 5: 0.025 32612 EuroCOVIDhub-ensemble 3
#> 6: 0.050 36068 EuroCOVIDhub-ensemble 3
#> 7: 0.100 41484 EuroCOVIDhub-ensemble 3
#> 8: 0.150 47110 EuroCOVIDhub-ensemble 3
#> 9: 0.200 50929 EuroCOVIDhub-ensemble 3
#> 10: 0.250 54561 EuroCOVIDhub-ensemble 3
#> 11: 0.300 57739 EuroCOVIDhub-ensemble 3
#> 12: 0.950 1464 epiforecasts-EpiNow2 1
#> 13: 0.975 1642 epiforecasts-EpiNow2 1
#> 14: 0.990 1951 epiforecasts-EpiNow2 1
#> 15: 0.010 28999 EuroCOVIDhub-ensemble 3
#> 16: 0.025 32612 EuroCOVIDhub-ensemble 3
#> 17: 0.050 36068 EuroCOVIDhub-ensemble 3
#> 18: 0.100 41484 EuroCOVIDhub-ensemble 3
#> 19: 0.150 47110 EuroCOVIDhub-ensemble 3
#> 20: 0.200 50929 EuroCOVIDhub-ensemble 3
#> 21: 0.250 54561 EuroCOVIDhub-ensemble 3
#> 22: 0.300 57739 EuroCOVIDhub-ensemble 3
#> quantile prediction model horizon